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Revecore

Team Lead, AI Engineering

Revecore

4h ago

0DevUnited Stateshimalayas
AI-Engineering-LeadLead-AI-EngineerLead-AI-ML-EngineerAI-ML-Engineering-LeadLead-AI-ML-EngineeringLead-AI-&-Analytics-EngineerAI-Team-LeadLead-AI-Product-EngineerMid-levelSenior

Job Description

Role OverviewWe are looking for an experienced Team Lead to guide our Core AI Agentic Development Team. This role demands a dual focus: maintaining a hands-on technical presence while providing mentorship, architectural guidance, and leadership to a team of Senior AI Engineers. The Team Lead will oversee the end-to-end development of complex, orchestrated agentic systems aimed at revolutionizing healthcare revenue cycle management and optimizing accounts receivable processes.What You Will DoLead the design and delivery of scalable, multi-agent AI systems, providing architectural direction for complex agent orchestration and enterprise integration. Oversee end-to-end development of agentic applications, ensuring alignment with business goals, performance standards, and healthcare revenue cycle requirements.Why It Might Be a FitThe ideal candidate will demonstrate the same elite technical skills expected of our Senior AI Engineers, including advanced Python proficiency, production LLM deployment, and mastery of orchestration frameworks like crew.ai. Furthermore, the candidate must possess deep technical knowledge in building scalable agent architectures, focusing heavily on system integration, guardrails, and governance.RequirementsAdvanced Python proficiencyProduction LLM deploymentMastery of orchestration frameworks like crew.aiDeep technical knowledge in building scalable agent architecturesArchitecting robust multi-agent orchestration systemsLeading the development of agents that interact with legacy and modern systems via APIs, computer use (UI automation), and voice AIEstablishing rigorous agent governance and safety guardrails to ensure compliance and reliability in productionGuiding software development teams through the entire product lifecycle using agile methodologiesConducting rigorous code reviews and establishing engineering standards specifically for agentic application developmentMentoring engineers and fostering a culture of continuous learning around rapidly evolving AI technologiesCollaborating with cross-functional stakeholders to translate complex requirements into actionable technical architecturesBenefitsPaid training and incentive plansMedical, dental, vision, and life insurance benefitsExcellent work/life balanceEmployee Resource Groups401(k) contributionsCareer growth opportunities12 paid holidays and generous paid time offOriginally posted on Himalayas